Interactions of individual and pair programmers with an intelligent tutoring system for computer science

Abstract

Pair programming is a practice where two coders work side by side at one computer. The practice has been linked to many benefits including increased student engagement, satisfaction, and course grades. We present a quantitative study comparing the fine-grained interactions of individual programmers versus pair programmers as they work to solve coding problems using an Intelligent Tutoring System. We collected data from over 115 students resulting in more than 53,000 log events. We discovered that while both individual and pair programmers had equivalent learning gains, pair programmers took significantly less time on most problems, consulted fewer examples, coded more efficiently, and showed more signs of engagement. Individuals adapted to problems requiring new and compounded concepts at a rate similar to pair programmers.